search for: infants

Hello all, A really noddy question for you all: I''m trying without success to do some subhypothesis testing. Using simple anova model, with a toy dataset from a book. I have four factors A,B,C,D, and wish to test mu_C = mu_D. This is what I have tried: > contrasts(infants$group,how.many=1) <- c(0,0,1,-1) > contrasts(infants$group) [,1] A 0 B 0 C 1 D -1 > fit <- aov(age~group,data=infants) > summary(fit) Df Sum Sq Mean Sq F value Pr(>F) group 1 0.740 0.740 0.2693 0.6092 Residuals 21 57.727 2.749...

I simply put, > NEVER=subset(infants$bwt,ISNO1) > UNTILPREGNANT=subset(infants$bwt, ISNO2) > ONCENOTNOW=subset(infants$bwt, ISNO3) and I wanna combine those three. I do it like ISNO=NEVER&UNTILPREGNANT&ONCENOTNOW and R tells me 1: In NEVER & UNTILPREGNANT : longer object length is not a multiple of shorter obj...

Hi I have three steps like this: Given ''a user called "$name" of type $user_type and status $user_state in organisation "$organisation_name"'' do |name, user_type, user_state, organisation_name| $runs ||= 1 puts "MOO #{$runs}" $runs += 1 # ... end Given ''a user called "$name" with username

Dear All, I am trying to graph a simple scatter plot where the x axis is year and the y axis is a percentage (percentage of infant death). Instead of plotting the raw data, I want to plot summary statistics such as mean and median. Here is the problem: the value range of y is between 0 and 1, but since infant death is a rare event, the mean and median is very low (something like 5%), which shows

Hello, In a study exploring transgenerational transmission of anxiety disorder we investigate whether infants react to experimentally induced mood changes of their mothers. We measured the time that an infant needed to cross a cliff (=crossing time) depending on whether his mother had previously undergone a mood induction (treatment) or not (control). The treatment is thus a within-subjects factor...

Hello, I have been trying for weeks to compile a 64-bit Rblas. I started with ATLAS where I have had success in the past, but 64 bit was not behaving, and as each compilation takes between 9 and 12 hours, "test, check, and revise" was not going to be really viable. I therefore switched to OpenBLas (OPBL). I was successful in compiling R-3.0.1 and an OPBL-based BLAS for Windows 64bit

>From k.j.mcconway@open.ac.uk Wed Mar 28 16:46:49 2001 Hardly crucial, but I've come upon a potential error in the documentation of the 'swiss' datafram in the R base package. The description accurately matches what is said in the Mosteller and Tukey source quoted, but according to the data archived at Princeton (links from http://opr.princeton.edu/archive/eufert/switz.html), the

Dear developers, I just noticed that step() function currently prints the current model using message(), but the resulting model using print(). The relevant commands within the step() body are: if (trace) message("Start: AIC=", format(round(bAIC, 2)), "\n", cut.string(deparse(as.vector(formula(fit)))), "\n") (with example() output:) Start: AIC=190.69

No, you're quite right, I was wrong. I must have been very confused when I put up the first 'bug' report, #886. I noticed my error a couple of days after and put up a comment to that effect on R-bugs, but it seems to have vanished (or alternatively I did that wrong as well). I agree with you on the criterion for the choice of districts as well. There remains a minuscule discrepancy

At times we want to convert a two-sided formula to a one-sided formula. In S we can do this by dropping the second entry in the formula. In R that object no longer has a formula class. R> ttt <- score ~ age | Infant R> class(ttt) [1] "formula" R> length(ttt) [1] 3 R> ttt[-2] [[1]] ~ [[2]] age | Infant R> class(ttt[-2]) NULL R> do.call("~",

We are trying to read a sas export file into R. (Works fine on Mac by ftping the export file from solaris box and then importing to R with read.xport, this gives rational numbers etc.) Trying to do this on an IBM Power p655 running linux, reading the same sas export file as used on MAC, in this case the results are not rational. Many of the numbers are interpreted as INF etc. Is it possible

I wanted to test if there exists already a name (which is incidentally a substring of another name) in a dataframe. I did e.g.: > data(swiss) > names(swiss) [1] "Fertility" "Agriculture" "Examination" "Education" [5] "Catholic" "Infant.Mortality" > ! is.null(swiss$EduX) [1] FALSE > !

Hi! I'm using nut to control a ups powerware 9135. All are working, but, in the shutdown, the ups don't poweroff. I did check with upsc, and I can't see a ups.delay.shutdown variable to set the time of automatic poweroff, when I did complete the shutdown of machines. Before, I did use a propietary program to work with this ups, and the daemon did poweroff the ups without problems. But,

Full_Name: Kevin McConway Version: 1.2.2 OS: WinNT Submission from: (NULL) (137.108.11.58) Hardly crucial, but I've come upon a potential error in the documentation of the 'swiss' datafram in the R base package. The description accurately matches what is said in the Mosteller and Tukey source quoted, but according to the data archived at Princeton (links from

Hi, I have this table (BTW, published by FBI and representing age distribution of the WTC tragedy victims): "LABEL" "FREQ" "MIDPOINT" "1" "Infant (under 1)" 0 "2" "1 to 4" 5 "3" "5 to 8" 1 "4" "9 to 12" 3 "5" "13 to 16" 0 "6" "17 to

Hello. I am trying to write an R function to plot the survival function (and associated hazard and density) for a Siler competing hazards model. This model is similar to the Gompertz-Makeham, with the addition of a juvenile component that includes two parameters---one that describes the initial infant mortality rate, and a negative exponential that describes typical mortality decline over the

I'm aware that S N Krishna asked the same question. However, I have failed to implement the posted solution for running rank order correlations on multiple subsets of data using the by() function. Here is my problem: Take a set of data from two subjects, who provided numerical infant mortality (IM) estimates for five countries: sub <- c(1, 1, 1, 1, 1, 2, 2, 2, 2, 2)

Dear all! I tried to fit Gompertz growth models to describe cummulative germination rates using nls. I used the following code: germ.model<-nls(percent.germ~a*exp(-b*exp(-k*day)),data=tab,start=list(a=100,b=10,k=0.5)) My problem is that I want that the fitted model goes through the origin, since germination cannot start before the experiment was started, and y-max should be 100. Does anyone

hello, I'd like know how to sort a data frame in R for example how I should do to sort by Catholic with swiss data frame like below thanks Fertility Agriculture Examination Education Catholic Infant.Mortality Courtelary 80.2 17.0 15 12 9.96 22.2 Delemont 83.1 45.1 6 9 84.84 22.2

...(such as the amount of a hormone administered) to a dependent variable (such as the height of a cornstalk). Its output was a model that could state, "for every 10% increase in the hormone, the height increased by X%." The zelazo data are the ages at walking (in months) of four groups of infants, two controls and two experimentals subjected to different exercise regimens. I don't understand why lm() can be used at all in this circumstance. My initial attempt was to use t.test(), which the answer key does also. I would have never thought to use lm() except for the requirement in the pro...